Cmpe 589 Spring 2006. Software Process Improvement Based on CMM Model Purpose of model Building –Reuse or build a model to help provides insights into.

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Presentation transcript:

Cmpe 589 Spring 2006

Software Process Improvement Based on CMM Model Purpose of model Building –Reuse or build a model to help provides insights into complex process behavior –support planning, tracking and prediction of software process improvement activities – Help evaluate different approaches

System Dynamics System dynamics was originally created to help better understand and control industrial systems. System dynamics is used –to model problems, –to address problems being experienced by any system that changes over time.

Approach existing Systems Dynamics models on SPI. –The Burke’s model, from his “Radical Improvements Require Radical Actions: Simulating a High3 –Maturity Software Organization” technical report (CMU/SEI-96-TR-024) can be chosen for process improvement, because of its close relationship of a SPI model to the CMM concept.

Modeling Process find the quantitative value of improving from CMM Level 3 to Level 5 “Experience Factory.” Determining the impact of various management-level policy decisions were discovered and then modeled.

Modeling Process “Experience Factory” vs. CMM Simulate high-maturity then working backward vs. Simulate lower-maturity then working forward Two types of SPIs : major & minor vs. KPAs in CMM

Burke’s study and model the software development and process improvement processes used by the NASA Goddard Space Flight Center (GSFC) Software Engineering Lab (SEL):

Burke’s study and model 1.Major software process improvement (SPI) efforts are piloted and deployed based onproject cycle time (i.e., pilot on one project, tailor and deploy on the subsequent project). 2.Major SPIs increase maturity (the probability of successfully achieving your goals). 3.Increased maturity attracts new hires and retains experienced staff that are “pro SPI” (i.e., they support and participate in SPI activities and are attracted to success and innovation). 4.Pro-SPI staff make minor SPI suggestions. 5.Major and minor SPIs decrease cycle time. 6.Decreased cycle time enables more major and minor SPIs to be accomplished. 7.Go back to 1 and repeat the cycle.

Life-Cycle process how software size, effort, quality, and schedule related to each other in order to produce a product. They could be changed by process improvements or by each other as one process improvement rippled through the four attributes. SPI benefits are modeled as percent reductions in size, effort, error rate or schedule.

The people process attitudes of project staff that affected the potential benefit of process improvement:: pro- SPI people, con-SPI people, and no-care people. The attitudinal mix and the pro/con ratio can affect the overall potential benefit realized by a SPI effort. This was defined as the attitude impact. It also assumed that it takes one project cycle for a new hire to become considered experienced. That is, the project cycle time is the learning curve.

Processing of maturity Level 4 and 5 KPAs Modeled the timing of the flow of process improvements into the life-cycle and people subsystems. There are two types of SPIs –major and –Minor The total maturity was defined as being a composite of major SPI maturity and minor SPI maturity. Each of these was set on a scale of zero to one.

Model modifications Major assumptions Life-Cycle process The people process

KPA process moving from CMM Level 2 to Level 3. –There are 7 major SPIs (7 level 3 KPAs under CMM model) has to be piloted and deployed by projects, in order to reach the next level of maturity Based on CMM assessment criteria, all KPAs must be implemented (piloted), plus some need to be repeated (deployed) to satisfy the institutionalization requirements.

KPA process

User interaction Model High Level Diagram

Model Verification and Validation Sensitivity Analysis –used to determine how “sensitive” a model is to changes in the value of the parameters of the model and to changes in the structure of the model. –indicate which parameter values are reasonable to use in the model.